# -*- coding: utf-8 -*-
import pandas as pd;

keywords=pd.read_csv('./dataset/keywords.csv')



moviesinfo=pd.read_csv('./dataset/movies_metadata.csv')

ratings=pd.read_csv('./dataset/ratings.csv')

ratings.groupBy('movieId')

ratings.groupBy('userId')
(rating, count)       45115 non-null float64
(rating, mean)        45115 non-null float64
(rating, std)         37456 non-null float64
(rating, min)         45115 non-null float64
(rating, 25%)         45115 non-null float64
(rating, 50%)         45115 non-null float64
(rating, 75%)         45115 non-null float64
(rating, max)         45115 non-null float64
(timestamp, count)    45115 non-null float64
(timestamp, mean)     45115 non-null float64
(timestamp, std)      37456 non-null float64
(timestamp, min)      45115 non-null float64
(timestamp, 25%)      45115 non-null float64
(timestamp, 50%)      45115 non-null float64
(timestamp, 75%)      45115 non-null float64
(timestamp, max)      45115 non-null float64
(userId, count)       45115 non-null float64
(userId, mean)        45115 non-null float64
(userId, std)         37456 non-null float64
(userId, min)         45115 non-null float64
(userId, 25%)         45115 non-null float64
(userId, 50%)         45115 non-null float64
(userId, 75%)         45115 non-null float64
(userId, max)         45115 non-null float64